System and method for ischemia classification with implantable medical device

ABSTRACT

An implantable medical device monitors ST segment data collected from EGM. ST trends are established and monitored over time. The IMD is able to discern whether the data indicate supply ischemia, demand ischemia, or other physiological causes. The IMD is then able to provide appropriate information and alerts.

BACKGROUND OF THE INVENTION

The present invention relates to medical devices and more particularly,to implantable medical devices.

DESCRIPTION OF THE RELATED ART

The heart pumps blood via the arteries to deliver oxygen to all portionsof the body. Like any other organ or tissue structure, the heartrequires oxygen and includes coronary arteries to facilitate thedelivery of oxygenated blood to cardiac tissue. Unlike other organs, adisruption of the oxygen supplied by the coronary arteries often resultsin discernable electrical parameters. These electrical parameters mayindicate ischemia or infarct and may also indicate the relative severityof the event.

A standard, 12 lead surface ECG (electrocardiogram) records electricalsignals across multiple vectors and produces a highly accuraterepresentation of cardiac data. Each cardiac cycle is distinctlyrepresented. A P wave is indicative of atrial depolarization, a QRScomplex is indicative of ventricular depolarization and a T wave isindicative of ventricular repolarization. The portion of the signalbetween the QRS complex and the T wave is referred to as the ST segment.An elevation of the ST segment from a relative baseline is typicallyindicative of a complete and sudden coronary occlusion whereas adepression of the ST segment is indicative of another form of ischemia,such as demand ischemia. For example, a coronary artery may be partiallyoccluded, allowing sufficient blood flow under normal physiologicalconditions. When physiological demand increases, such as duringexercise, the cardiac tissue receives insufficient oxygen, becomingischemic. Typically, cessation of the activity reduces demand and as thesupply becomes sufficient the ischemia resolves and this is indicated bythe ST segment returning to the baseline value.

As indicated, the surface ECG provides accurate and detailedinformation. In addition, the data is often redundant as each channelthat is recorded represents the same events as they occur over differentvectors. A physician can therefore check multiple channels whenevaluating the data for increased reliability and accuracy.

Implantable medical devices (IMD) often include sensors that detectelectrical cardiac signals. When collected internally (as opposed to onthe surface (i.e., ECG)), these signals are referred to as anelectrogram (EGM). Due to their size and placement, the IMD typicallywill only record data over one or two distinct vectors. Furthermore, thecathode and anode of a given sensing pair may be relatively closetogether. For example, a tip electrode and a ring electrode on a commoncardiac lead sense electrical signals across a small portion of theheart. The device housing may include one or more electrodes. Thus,sensing from e.g., a tip electrode or coil electrode to the housing(“can”) electrode provides a vector across a greater portion of theheart. These examples relate to implantable pulse generators (IPGs),often referred to as pacemakers or low power devices and implantablecardioverter/defibrillators (ICDs), often referred to as high powereddevices, which may also include pacing functionality. IPGs and ICDstypically include a housing implanted subcutaneously or submuscularlyand connected to one or more leads that transvenously enter the heart.Other devices, such as an implantable loop recorder (ILR) are implantedsubcutaneously to record data, but do not include leads extending to orinto the heart. For example, the Medtronic Reveal™ includes spacedelectrodes on the housing. The EGMs collected are extremely useful fornumerous reasons; however, they are limited in certain circumstances anddo not necessarily provide the same level and types of information assurface ECG data.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is a schematic illustration of an implantable medical device(IMD) with a lead extending into a heart.

FIG. 2 is a schematic illustration of an IMD having a lead extendinginto a heart and a lead extending to a spine.

FIG. 3 is a block diagram of selected components of an IMD.

FIGS. 4A-4C illustrate exemplary ECG tracings.

FIG. 5 illustrate an EGM tracing.

FIGS. 6A-6D illustrate ST variations obtained from EGM data.

FIGS. 7-10 are flowcharts of processes consistent with the teaching ofthe present invention.

DETAILED DESCRIPTION

FIG. 1 illustrates the placement of an exemplary implantable medicaldevice (IMD) 10 within a patient 8. IMD 10 is illustrated as animplantable cardioverter/defibrillator (ICD); however, it should beappreciated that IMD 10 may be an IPG, ILR, drug delivery device, spinalstimulator, neural stimulator, or other implantable device so long as itis capable of sensing electrical cardiac signals. The IMD 10 includes ahousing 30 with a header 32 attached thereto. One or more electrodes 34a, b, c, d (collectively 34) may be included and disposed about variouspositions on the housing 30; including along an outer perimeter and/oron any portion of a major face of the device including utilizing theentire can as an electrode. A lead 14 is illustrated as being coupled tothe housing 30 via the header 32. It should be appreciated that morethan one lead may be employed.

The lead 14 enters the vasculature through the superior vena cava (SVC),passes through the right atrium and enters the right ventricle (RV). Thelead 14 includes an SVC coil electrode 16, an RV coil electrode 18, aring electrode 20, and a tip electrode 22. A given lead may include oneor more of these electrode or electrodes in other configurations. Anytwo electrodes may serve as the cathode and anode and provide a vectorto obtain EGM data. As previously indicated, a vector from, e.g., the RVcoil electrode 18 to one of the can electrodes 34 crosses a largeportion of the heart 12.

FIG. 2 illustrates another embodiment of IMD 10. In this embodiment, alead 40 is placed within the heart 12. In addition, a lead 42 is coupledwith the patient's spine 50. The lead 42 may deliver electricalstimulation to the spine 50 and/or serve as a mechanism to deliver adrug to the spine 50.

FIG. 3 is a block diagram illustrating various components and/or modulesthat may be included in any combination in a given IMD 10. Numerousaspects of the IMD 10 are conventional, with many not being illustratedherein and with others not explained in detail. The IMD 10 includes apower supply 60, typically a battery. A microprocessor 62 and memory 64are included. A communication module 66 is provided so that IMD 10 maycommunicate via telemetry with an external medical device 114 such as amedical device programmer or other external interface. The communicationmodule 66 also permits communication with remote sensors 110 implantedin other location(s); alternate IMDs 112 implanted in other locations(e.g., a drug pump); or patient worn or carried external devices,sensor, or inputs.

The IMD 10 may include an accelerometer 68 (or multiple accelerometers)that can be configured to provide positional data (e.g., prone,standing, etc.) and/or activity level data 72. A heart rate monitoringmodule 74 is illustrated. EGM data can readily be utilized to obtainheart rate data and the module 74 illustrates the software, hardware,and/or firmware to provide this data. A respiration monitoring module 76is provided to generate data related to breathing parameters. Animpedance based sensor may be used to measure impedance changes throughthe chest cavity to establish breathing. Breath rate is output from ratemodule 78. Sensors may be provided to determine effects of respirationvia an oxygen saturation module 80 or tissue perfusion module 82.

An EGM analysis module 84 is provided. This module analyzes EGM data to,in particular, establish ST segment patterns as will be described ingreater detail. Sensor inputs 86 and 88 simply illustrate the input of aone or more data sources into the IMD 10. For example, a sensor inputmay be a lead coupled to the device, an electrode coupled with thedevice, or some other sensor. A given IMD 10 may include numerous sensorinputs. The IMD 10 is illustrated as having a temperature sensing module90 and in particular an esophageal temperature sensing module 92.Various internal temperatures may be monitored from that of blood withinthe heart to temperature changes made by ingesting food or fluidsthrough the esophagus. A pressure sensing module 95 senses fluidpressure within various anatomical locations, such as within a portionof the heart. A chemical sensor 97 may be provided that senses thepresence or quantity of a particular substance such a potassium, Creactive protein, or other substances. Working with the EGM analysismodule is an ST analysis module 94 that further utilizes EGM data toestablish, evaluate and utilize ST segment data.

As will be explained in greater detail, the ST segment data may indicatevarious physiological conditions. Some of these conditions may warrantimplementing or changing a therapy provided by the IMD 10 (if any).Therapy module 96 modifies the therapy parameters based on the indicateddata, independently or via instruction from a clinician. If the IMD 10has a therapy capability, it is represented by the therapy module 98,which may include, for example, a pacing module 100 and/or a high powermodule 102 for defibrillation.

FIGS. 4A-4C are stylized ECG tracings illustrative of various cardiaccycles. FIG. 4A is meant to nominally illustrate a “normal” cardiaccycle. As previously indicated, the P wave is a representation of atrialdepolarization. After an AV delay, ventricular depolarization begins,which is indicated by the QRS complex. Finally, the T wave is indicativeof repolarization of the ventricles. The various intermediary sectionsmay be represented differently depending upon convention. The PRInterval is shown as beginning with initiation of the P wave andterminating with initiation of the QRS complex. While readily apparentin these stylized representations, such delineation is not always soreadily apparent in reality. The isoelectric portion between the P waveand the QRS complex is referred to at the PR segment. The QT intervalbegins with initiation of the QRS complex and ends with termination ofthe T wave. Often, the QRS complex is referred to as an R wave;particularly when sensed internally as this is the dominant component.Furthermore, the peak of the R wave is an identifiable marker that willbe referred to hereinafter.

The ST segment begins with the termination of the QRS complex and endswith the initial deflection of the T wave. Normally, the ST segment isisoelectric. There may, however, be a difference or delta between thevalues of the PR segment and the ST segment and is referred to as the STdeviation 400. The ST deviation 400 should be relatively constant; thatis, factors that would shift the PR segment will similarly shift the STsegment.

FIG. 4B is a stylized ECG tracing illustrating an elevation in the STsegment as compared to FIG. 4A. Such an elevation is an indicator ofpotentially serious ischemia or infarct. That is, when a completecoronary occlusion occurs, there is an elevated ST segment. Thus,hospitalization and invasive and/or pharmacological therapy may bewarranted.

FIG. 4C illustrates ST segment depression. ST segment depression is aless specific indicator and may relate to demand ischemia or otherrelatively stable conditions that do not necessarily require immediateintervention. For example, a partially occluded artery may permitsufficient blood flow under normal physiologic conditions. Withincreased demand, e.g., during exercise, this artery does not providefor the increased oxygen needs of the relevant portion of the heart. Assuch, that portion of the heart is ischemic; however, upon cessation ofthe activity the demand is reduced and the ischemia resolves. In suchcases, the patient may be monitored, advised to alter activities, orgiven various drug therapies.

As indicated, these are stylized representations. True ECG tracings aremore complicated to evaluate and require some skill on the part of theclinician. Furthermore, with a 12 lead ECG there are multiple channelsto evaluate. Thus, if one vector does not clearly demonstrate aparameter, another may. In addition, the multiple vectors can aid inconfirming an evaluation.

FIG. 5 is a stylized representation of an electrogram (EGM), which is arepresentation of the electrical cardiac signal sensed by an implantabledevice (such as IMD 10). IMD 10 may include multiple electrodes disposedin various positions. At the very least, the IMD 10 will include atleast two electrodes spaced sufficiently far apart that cardiac eventsare sensed. As indicated, a therapy device such as an IPG or ICD thatincludes leads provides multiple electrode positional opportunities withspatial diversity. A subcutaneous implantable loop recorder may have alimited number of integral electrodes, positionally limited by thedimensions of the device housing. As such, device positioning uponimplant will affect the signals sensed.

The EGM of FIG. 5 is meant to illustrate a normal cardiac cycle likethat of FIG. 4A. The P wave is illustrated; however, it should beappreciated that due to the relatively small amplitude of this waveform,it may not be apparent in many EGMs. The R wave is a dominant featureand is typically identifiable, with varying degrees of detail regardingthe overall QRS complex. The T wave, like the P wave may or may not bediscernable.

The EGM does illustrate a delta between the PR segment and the STsegment, which is ST deviation 500. Though not illustrated, the variousischemic events will produce changes in the EGM; however, these changesdo not necessarily correlate to their counterparts in an ECG. That is,if in a given cycle the ECG would indicate ST segment elevation the EGMmay or may not indicate the same, may indicate depression, or may notpresent a discernable change in a given cycle. Thus, the same general“rules” that apply to ECG analysis may not apply to EGM analysis. Thus,sensed ST segment elevation may not reliably indicate a seriouscondition and ST segment depression may not reliable indicate a lessserious condition and may in fact occur due to the more seriouscondition.

As will be discussed in further detail, embodiments of the presentinvention utilize trend information about ST segments over multiplecardiac cycles. FIG. 5 illustrates several factors used to identify therelevant ST point 505 (STP) and controls for normal variations. The peak510 of the R wave is identified as a reference point. A predeterminedperiod of time R-STP (e.g., 80, 90, or 100 ms) is added to the peak 510to calculate the ST point 505. In other words, the R wave of the QRScomplex is identified and using known cycle parameters, a (heart ratemodulated) period of time is added so that the selected ST point 505likely falls within the ST segment. It should be appreciated thatvarious other mechanisms may be utilized instead in order to label thispoint, such as adding a period of time to the end of the QRS. Forexample, an analysis of QRS width may be done for each cycle orperiodically in order to determine a patient specific value to add tothe determined peak. Alternatively, the subsequent P wave may bediscernable and time subtracted from this event. The ST point 505 simplyneeds to be a point that falls within the ST segment with sufficientreliability and any mechanism that achieves this is acceptable.

As previously indicated, there may be isoelectric ST deviation 500relative to the PR isoelectric level. Thus, embodiments of the presentinvention also identify a PR point 515 (or PRP). Again, this is simply apoint that occurs in the isoelectric segment between the end of the Pwave and the initiation of the QRS complex. In one embodiment, pointsare selected moving backwards from the peak 510 until a determined slopeis zero or two temporally separate points have substantially the samevalue. Alternatively, a predetermined value (of time) is subtracted fromthe peak 510, again with reasonable reliability that the PRP will bewithin the PR segment.

Once the PRP is determined, the measured electrical value (milivolts) issubtracted from the measured STP. Thus, the resultant ST point is takenfrom an isoelectric baseline so that collected data points correlate. Agiven measured ST point will be referred to as a measured STP and agiven ST point correlated with the isoelectric baseline will be referredto as a correlated STP.

Correlated STPs are collected over time and analyzed. This analysisillustrates trends that are then used to identify clinical events. FIGS.6A-6C illustrates graphs of the collected correlated STPs over time. Inthese figures, time t(A) is the time at which the correlated STP exceedsa threshold value. The correlated STPs are either absolute values of thedata point or alternatively (and not illustrated) if negative valuesarise, then the graph is inverted and threshold crossings, maximums,etc. are correspondingly inverted. When the threshold is crossed att(A), a timer is initiated and runs until time t(B). This defines aperiod of time of analysis. In one embodiment, this period of time isapproximately 10 minutes. At time t(C), the correlated STP reaches amaximum value (relative to the time period t(A) to t(B)).

The graph of FIG. 6A represents a non-ischemic ST segment variation. Forexample, posture changes may have an effect on ST values. Thecharacteristics of this type of event include a large slope; that is themaximum is reached quickly. The resultant correlated STP holds steadyfor a given period of time. In other words, an event occurs that veryrapidly changes ST values from one relatively steady state to adifferent, relatively steady state. Similarly, a very rapid changeoccurs returning the correlated STPs to their baseline values.

FIG. 6B is a graph that represents a serious, sudden onset supplyischemia (e.g., occlusion of a coronary artery) that if untreated (ordoes not resolve itself) will lead to an acute myocardial infarction(AMI). This is potentially a very serious condition and warrantsidentification. Exemplary algorithms for determining the nature of theapparent ischemia will be discussed below. A general description beginsagain with the correlated STP crossing the threshold. The threshold is avalue below which variation in the correlated STP is considered normal.That is, while illustrated as a constant baseline, the correlated STPsmay have some variation, or noise, without indicating a problem. Whilenon-limiting, the threshold in one embodiment is 0.1 mv.

At time t(A) the correlated STP exceeds the threshold and the timer(running until t(B)) is initiated. This represents the period of timethat will be evaluated and after which a conclusion will be drawn. Attime t(C), the correlated STP reaches a maximum value (for the intervalbetween t(A) and t(B)). The maximum should be reached relatively quicklyto evidence an occlusion but not so quickly as to indicate an innocuousevent such as a posture change. After reaching the maximum, thecorrelated STP levels should remain relatively high through t(B), thoughthey may drop somewhat and still be considered indicative. If thecorrelated STPs return to their baseline values (or close thereto) at orbefore time t(B), this likely indicates one of two things. Either, thisevent was a vasospasm where for some reason the artery constricteditself for a brief period of time and then relaxed or there was acoronary occlusion that resolved itself. Both instances may be notableevents that should be recorded and presented to a physician. The laterevent, i.e., a self resolving coronary occlusion is likely indicative ofa clot or plaque that occluded the artery then passed through. Thismaterial remains in the arterial system and may present a risk ofthrombosis. In general, if the correlated STPs reach a maximumrelatively quickly and remain deviated, this is taken as an indicationof ischemia caused by a sudden coronary occlusion that will likely leadto an acute myocardial infarction.

FIG. 6C a non-specific ischemia. Notably, the values from the baselinemay be positive or negative again illustrating that a comparison withsurface ECG deflection or elevation is may or may not be reliable. Here,the values gradually rise to reach a maximum. Though not dispositive andnot illustrated to scale, this maximum value is likely less than themaximum of e.g., FIG. 6B, although necessarily greater than thethreshold value. FIG. 6C also illustrate some fluctuation after reachingthe maximum and though not illustrated, the values may continue toincrease after time t(B). This indicates that a non-specific ischemiamay be occurring as a result of a drug, a chemical imbalance (e.g.,potassium deficiency), or the like.

FIG. 6D similarly illustrates a non-specific ischemia wherein themaximum is reached later in the time period t(A) to t(B), thusdifferentiating it from supply ischemia. Further, the values return tobaseline in a relatively short period of time. The evaluation periodt(A) to t(B) is in one example, 10 minutes. Demand ischemia occurs if apatient having a partial occlusion increases their level of exertion,such as during exercise. As exertion increases, the body demands moreoxygen and the heart works harder. In a similar fashion, the heart thendemands more oxygen, which the partially occluded artery cannot supply.The resultant ischemia causes angina and other discomfort to a levelthat precludes the patient from continuing at that level of exertion. Assuch, the patient will return to a lesser level of exertion, and theischemia will resolve. This is illustrated in FIG. 6D along with anexemplary graph of heart rate. In this scenario, the change in ST valueswill correspond or track with heart rate.

FIG. 7 is flowchart describing one process consistent with the teachingsof the present invention. As previously described, surface ECG andinternal EGM signals are both obtained from cardiac electrical data.However, while these signals both relate to the same physiological event(e.g., ventricular depolarization) they do may or may not both bepresent the same or even necessarily corresponding data. An IMD 10collects (700) EGM data for each of a plurality of cardiac cycles and atleast temporarily stores this data in memory. For each cardiac cycle,the IMD 10 identifies (710) a point within the ST segment for evaluation(STP). These points are compared and the IMD 10 determines if there hasbeen any change (720) in trend beyond a baseline or noise value. If nochange (720) is noted, then the IMD 10 simply continues to collect data(700). If a change is noted (720), then this trend data is classified todetermine what the trend data indicates such as, for example, anon-ischemic event, demand ischemia, or supply ischemia. Based upon theclassification (730), the IMD 10 will take (740) the appropriate action.Such actions may include without limitation doing nothing, noting theevent, recording data into memory, alerting the patient, alerting acaregiver, or providing therapy.

FIG. 8 is a flowchart that describes another process consistent with theteachings of the present invention. In steps 800-815 data is gatheredand a pattern is classified at step 820; however, the process ofclassifying the pattern occurs in steps 825-875 based upon the collecteddata. It should be further appreciated that the data collected (800-815)is not necessarily collected or processed sequentially nor necessarilyin the order presented. Various STPs are collected and a given valuecrosses a threshold to initiate a relevant time period. From theinitiation of the time period until a maximum STP value (during the timeperiod) is reached, the rate of transition or slope of the transition isdetermined (800). In addition, the time from initiation until themaximum is reached is determined (805). In other words, how long does ittake to reach the maximum STP, once the period is initiated. Thecorrelated ST value of the maximum value is identified (810). This isthe correlated ST value. The termination point is identified (815). Thisis not necessarily a separate step as the initiated time period is for apredetermined duration; hence, this point in time is thereforepredetermined. The correlated ST value at this endpoint (or the averagevalue of several points before, during and after this endpoint) isnoted.

Once these data points are determined, the pattern is classified (820).In a first branch, the duration of the transition (805) is too short(825). That is, the time interval from initiation of the time perioduntil reaching a maximum is too fast to be physiologic. Furthermore, ifthis branch is followed, the rapid transition is typically followed by arelatively constant rate. Thus, causes for this type of pattern may bean abrupt change in posture or the sudden ingestion of a cold fluid. Thespecific timing parameters are not meant to be limiting in the presentdescription and there may be some overlap at boundary conditions (whichmay be further analyzed as described hereinafter). As a generalguideline, a rapid transition that ranges from nearly instantaneous to afew seconds is “too” rapid to be ischemic. Transitions that extend to,for example, 30 seconds are likely too rapid. Again, non-ischemic causeswill tend to be very rapid and abrupt such as a posture change.Typically, this should present a very discernable temporal relationshipthat would not require subsequent analysis.

If the duration of the transition (805) is greater than a predeterminedvalue, then analysis proceeds along branch 840. Here, a point prior tothe maximum is identified. This may be a predetermined number of datapoints prior to the maximum, the time at which a predeterminedpercentage of the maximum is reached (e.g., 50%, 90%), or a time basedidentifier such as one half or three quarters of the duration (805).This is meant to uniformly identify some point along the transitionwherein taking the slope of this point will provide useful data. Forexample, once the maximum is reached the slope is likely 0, close to 0,or even negative. Thus, step 840 identifies a point prior to the maximumwherein the slope is taken and utilized.

If the slope is too low (855) this indicates demand ischemia (860) orsome other non-physiological cause and this classification is made(820). In other words, the rate of change is too slow to indicate supplyischemia. Conversely, if the slope falls within an indicative range,then the correlated ST value at termination point is evaluated. If thisvalue is above a predetermined threshold, then the pattern is classifiedas supply ischemia (875). If the value at the termination point is closeto the baseline value, then this indicates either a coronary occlusionthat self-resolved or vasospasm. Both events may be notable, but aredistinct from a classification of supply ischemia.

The description of parameters has been rather generalized to illustratethe broader concept and to illustrate that specific numericallimitations will vary based upon the selected evaluation parameters.FIGS. 9A and 9B present a more specific process consistent with theteachings of the present invention. In general, identifying the cause ofpatterns in the STP is useful whether it is determining a non-ischemiccause such as a posture change or a stable condition such as demandischemia. The most urgent condition is supply ischemia, which if leftunresolved will likely lead to an acute myocardial infarction. Thus, thepresent process is described in the context of ruling supply ischemia inor out as the primary concern. The flowcharts of FIGS. 9A and 9B will bedescribed with reference to the graphs of FIG. 6A-6D.

In the course of normal operation of the IMD 10, EGM data is collected(900) and processed. As previously explained, an ST data point isidentified for each (or once every several) cardiac cycle. This may be asingle point taken for each cycle or a number of points/measurementstaken during the ST segment and averaged together. The ST data for eachcycle is correlated to the baseline value by accounting for the STdeviation from the PR segment, which results (910) in the ST point(STP). As ST segment elevation or depression is not meaningful in thepresent context, the values may be used as they are taken or absolutevalues may be utilized.

The STP is compared (915) with a threshold value that is in excess ofwhat would be standard fluctuations or noise. While non-limiting, thethreshold in one embodiment is 0.1 mv. If the STP is below (915) thethreshold, then the process returns and continues to collect EGM data(900). If the STP exceeds the threshold (915), then the time of thisthreshold crossing is denoted (920) at t(A) and a timer of B minutes isinitiated (925) which will terminate at time t(B). In one embodiment,the timer is run for 10 minutes. The use of a timer is not mandatory,but allows for a specified endpoint and duration.

During the interval from t(A) to t(B), EGM data is collected (930) andprocessed in the same manner as in steps 900-910 so that an STP isprovided for each cardiac cycle. Each of these STPs is evaluated todetermine (935) if they all exceed the threshold value. In general, ifthe STP falls below the threshold value subsequent to initiating thetimer, this is an indication that the event was either not supplyischemia or was supply ischemia that self resolved. Thus, if the STPdoes drop below the threshold during the timer, the process reverts tonormal data collection (900). It should be appreciated that this mayoccur during the running of the timer (925) in which case the entireprocess in truncated or data is collected during the entire interval andall collected data is evaluated with a conclusion drawn at this point inthe process. Further, a certain percentage of the data points may needto be below the threshold for the process to conclude that there is notsupply ischemia. For example, if 90% or more of the data points exceedthe threshold value, this may satisfy this step (935). If, for example,80-90% exceed the threshold then the process might evaluate secondaryfactors rather than reaching a determination, whereas if less than 80%of the values exceed the threshold then a determination that supplyischemia is not present or ongoing is reached.

Assuming all or a sufficient number of STPs during the time periodexceed the threshold, then the maximum STP during this time period isidentified (940). The time that this maximum value is first reached isdenoted t(C). Next the interval from t(A) to t(C) is calculated andcompared with predetermined value D (945). If t(A) to t(C) is less thanD, then this overall change is too rapid to be supply ischemia andtherefore the process concludes that there is no ongoing supply ischemiaand returns to generally monitoring (900). Again, this is notnecessarily a literal return in that data is being collected; however,the conclusion is reached and the process is not attempting to continueto determine supply ischemia with this data set. The value D is a timeduration that would likely result from factors such as posture changeand the like that produce rapid transitions. Thus, while non-limitingsuch durations are likely on the order of a few seconds.

Assuming that the interval from t(A) to t(C) exceeds value D, then theprocess proceeds to step 950 in FIG. 9B. At this point, the process isgenerally attempting to discriminate between supply or demand ischemia,which will be primarily differentiated by the slope of the transitionprior to reaching the maximum. Taking the slope at the maximum orimmediately prior thereto might not produce meaningful data. Thus,another point E is identified. Point E occurs at the time t(E) (betweent(A) and t(C)) when the STP reaches a predetermined percentage of themaximum value. For example, when the STP is 90% of the maximum STP, thispoint is denoted as E and the slope is determined (955).

The slope or rate of change between t(A) and t(E) is evaluated andcompared (960) with a predetermined value. If the slope exceeds thisvalue, then the event is not likely to be supply ischemia. As apractical matter, this is the same or similar to that analysis at step(945). If the slope too low, then the rate of change is more indicativeof demand ischemia. Again, the specific values may be patient specificor population specific. The rate of change corresponding to an increasein demand due to exercise may likely take approximately two minutes ormore to reach a maximum.

If the slope is within the range (960), the final general criteria iswhether the STP at t(B) is sufficiently high to indicate (965) ongoingsupply ischemia. One mechanism for evaluating this parameter is todetermine if STP at t(B) exceeds some predetermined percentage of thevalue at t(C). That is, if supply ischemia is ongoing, the STPs maydecrease from the maximum but should still remain relatively highthrough the time period B. Thus, if at t(B) the STP is back to baselineor relatively low this would indicate that supply ischemia is notpresent (either another event such as vasospasm or the supply ischemiahas self resolved). Thus, if STP at t(B) is at least 50% of the maximumSTP, then the process indicates (970) that supply ischemia is present.The percentage value used may be appropriately selected. The higher thevalue, the greater the specificity of the process and the less like thata false positive will occur. While non-limiting, values from 40% to 90%in general and specific values of 50%, 75%, and 80% are included.

In general, a sudden, total coronary artery occlusion is serious and ifunresolved will likely lead to an acute myocardial infarction. Thus,there is a desire to accurately identify these events and encourageappropriate medical intervention. Conversely, there is also a desire notto generate false positives, unduly worry the patient and burden thecaregiver. Thus, as timelines, ranges and parameters are employed, theyshould be selected to ensure an appropriate reliability threshold.

In some instances, the data will be clearly indicative of a given issue.For example, if the STP changes from one relatively constant value toanother relatively constant value in one second, then this is quitelikely a postural change. Conversely, if a change occurs over a minuteand leads to a relative maximum that remains for an observation period,this is highly suggestive of supply ischemia. When a change occurs moregradually, reaches a peak and returns to a baseline, this is most likelyindicative of, for example, demand ischemia during exercise.

There are, of course, parameters that may be closer and harder todistinguish. For example, a vasospasm (a temporary arterial contraction)will lead to an increase in the STP values with a return to baseline.This may be difficult to discern from stable angina (e.g., demandischemia). Similarly, various factors may cause a more rapid increase(and hence slope) in a demand ischemia case or a less rapid increase ina supply ischemia. For example, an artery may become partially occludedfor a brief period and then become fully occluded. The point is thatsome situations will be harder to discern, particularly based upon thecriteria selected for inclusion or exclusion such as the required slope,the percentage of events above threshold, the value at the end of thetime period, the time to reach the maximum, etc.

In order to increase the specificity of the analysis, particularly inthese closer cases, various embodiments include secondary factors thatmay be utilized to rule in or rule out a conclusion. FIG. 6D illustratesone such example where the STP data for demand ischemia is plottedagainst an exemplary heart rate graph. As previously discussed, demandincreases as the patient increase their level of exertion. As thecoronary artery is unable to provide the necessary supply, angina ensuesand the patient becomes unable to continue or maintain the level ofexertion. As such, the patient decreases their level of exertion andconsequently, demand is reduced. This happens to track well with heartrate. Thus, heart rate monitoring may be used as a secondary factor toconfirm demand ischemia or rule out other conclusions. In cases ofsupply ischemia, vasospasm, or other ST variations there is unlikely tobe a direct correlation with heart rate. Other secondary factors mayinclude activity sensors to determine level of exertion or positionsensors to identify posture/position. Temperature sensors may be used todetect the ingestion of cold fluids. Pressure sensors may be used tomeasure blood pressure inside or outside of the heart. Respirationsensors such as impedance sensors may monitor breathing patterns. Thismay be used to indicate exertion but also shortness of breath may beindicative of an MI. Oxygen saturation may be monitored internally andsimilarly, tissue perfusion may be monitored by an optical sensor toindicate arterial oxygen supply. Finally, various chemical sensors maybe implanted. For example, a potassium imbalance will result in STvariation, typically gradually over time. Thus, potassium is but onesubstance that may be monitored. Other drugs have known effects on STvalues and may be monitored for with embodiments consistent with theteachings of the present invention. C reactive protein is a generalindicator of inflammation and if present, might cause borderline data toshift towards supply ischemia. In summary, various other sensor or datainputs may be confirmation of a determination of ST deviation.

FIG. 10 is a flowchart that illustrates potential actions that may betaken when an ischemic event is identified (1000). Initially, additionalinformation may optionally be collected (1005) to verify a determination(as discussed above), assess a level of severity, determine a patientlocation, or obtain alternative information including direct patientinput. Subsequently, the IMD 10 may determine an appropriate action orset of actions and implement (1010) those actions.

Though not illustrated, in any given situation the IMD 10 may take noaction. For example, an event monitored over a period of time that isultimately determined to be the result of a posture change does notnecessarily require any action. The most basic action that the IMD 10may take is to flag (1015) the event; that is, denote the event in somemanner. This will typically include storing data (1020) into memory forfuture retrieval or use. The data may include the raw data, the STPs,the conclusions, and/or the EGMs in the time period relevant to theevent. In some situations, this may be the only action the IMD 10 iscapable of providing, but this information may be later retrieved andutilized by a caregiver in any number of contexts.

The IMD 10 may notify (1025) the patient when a detection of ischemia ismade. Such notification could occur with an audible sound generated bythe IMD 10, a tactile sensation (vibrating), or communication throughand external electronic device such as a home monitor, pager, PDA,cellular/digital phone or the like. For demand ischemia, the IMD 10could notify the patient as exercise levels approach those that havepreviously caused ischemia. That is, the physical result of demandischemia will most likely provide an indication to the patient in a timeframe that causes them to alter behavior; however, as subsequent eventsbegin the patient could be alerted to avoid the situation.Alternatively, perhaps the demand ischemia is not perceptible or fullydisruptive to the patient and such an alert may make them aware of asituation that they would otherwise ignore to some degree.

The potentially more serious situation is supply ischemia. Thus, whenthe IMD 10 identifies supply ischemia the patient notification (1025)may have more urgency. For example, the patient upon receiving thenotification may proceed to an emergency room or request an ambulance.In some cases, there may be predetermined treatments such as takingpharmaceuticals to relax arteries, thin blood, and/or disrupt clots.

The IMD 10 may be communicatively coupled with an external informationnetwork. For example, a patient monitor may be coupled with a phone lineor computer network or the IMD 10 may communicate directly over acommunication pathway like a cellular or digital phone. In such a case,the IMD 10 may communicate (1030) with a clinician and/or communicate(1035) with emergency services to e.g., summon an ambulance.

To this point, the actions taken have been indirect. That is, adetermination is made, information is provided, and any subsequentaction taken is outside of the IMD itself. Depending upon the IMD'scapabilities, various actions may be taken. For example, a therapy maybe changed or added (1040). A defibrillation threshold may be adjusted(1045) in response to the noted supply ischemia and potential infarct sothat first shock effectiveness is maximized based upon the newcondition. Similarly, pacing thresholds may be changed (1048) to providea greater reliability of capture in anticipation of physiologicalchanges that could occur, otherwise raising the threshold of the tissue.

Another device change could include altering or disabling 1050 rateresponse (RR). Rate response is the ability of an IPG to vary pacingrate based upon perceived physiological need. With demand ischemia,reducing the upper pacing rate would preclude the heart from reaching arate deemed undesirable. With supply ischemia, avoiding higher rateswould require the heart to work less and hence avoid stressing the heartafter this condition is identified.

During either type of ischemia, the patient may experience pain orangina. The IMD 10 may include various pain alleviating mechanisms(1055) such as spinal stimulation or drug delivery (1060). That is, theIMD 10 may include a one-time or replenishable supply of pain relievingdrugs, as well as other pharmaceutical or biologic agents. Thesematerials may work to relieve pain, thin the blood, relax the arteries,dissolve occlusions, or promote corrective growth.

Other pacing therapies or variations can also be employed. Similar toadjusting rate response, the IMD 10 may implement an algorithm to reduceor minimize any unnecessary pacing (1065). This is under the assumptionthat if pacing causes propagation that results in the heart workingsomewhat harder due to the condition, avoiding such pacing may bebeneficial. Pacing may be deemed unnecessary either based on rate; thatis, simply pace less or by tolerating intervals (e.g., AV intervals)longer than normal to rely more heavily upon intrinsic conduction.

Another pacing option that the IMD 10 may provide when supply ischemiais detected is to pace to deliberately produce asynchronous contractions(1070). In some cases, this may provide a cardio-protective benefit. Ina normal contraction, the ventricles should depolarize and contract in agenerally coordinated manner to maximize efficiency and output. If someportion of the heart in infarcted, that tissue no longer depolarizes andcontributes to the contraction. Thus, the tissue surrounding theinfarction must work that much harder. When there is a synchronizedcontraction, each portion of the heart muscle is contracting (throughfluid) against similarly contracted tissue. In an asynchronouscontraction, the contracting portion is contracting against a relaxedportion of the heart. Thus, the contracting portion is not encounteringas much resistance and works less. Cardiac output may not be asefficient or optimized, however, as a short term therapy it may proveuseful and even as a longer term therapy in some cases.

Various embodiments consistent with the present invention have beenillustrated and described. It should be appreciated that the presentinvention is not limited to the embodiments described nor to theparticular arrangement of elements, steps or sequences and one ofordinary skill in the art will understand the variation of the describedembodiments are within the spirit and scope of the present invention asset forth in the claims.

The invention claimed is:
 1. A method comprising: obtaining anelectrogram representing cardiac data from an implantable medical devicefor a plurality of cardiac cycles during a period of time; monitoringheart rate during the period of time; determining an ST segment datapoint for each of the cardiac cycles; evaluating the ST segment datapoints; determining whether the evaluated ST segment data pointsindicate supply ischemia; determining whether a trend of a plurality ofthe ST segment data points tracked a trend of a corresponding pluralityof monitored heart rates during the period of time; and confirming thedetermination of whether the evaluated ST segment data points indicatesupply ischemia based on whether the trend of the plurality of STsegment data points tracked the trend of the plurality of monitoredheart rates.
 2. The method of claim 1, further comprising ruling out adetermination of supply ischemia when the trend of the plurality of STsegment data points tracked the trend of the plurality of monitoredheart rates.
 3. The method of claim 2, further comprising detectingdemand ischemia when the trend of the plurality of ST segment datapoints tracked the trend of the plurality of monitored heart rates. 4.The method of claim 1, further comprising evaluating a secondaryindicator to confirm the determination of whether the evaluated STsegment data points indicate supply ischemia, wherein the secondaryindicator includes a respiration rate and an activity sensor.
 5. Themethod of claim 4, wherein supply ischemia is indicated if indicated bythe ST segment data points and an increased respiration rate is sensedwithout a corresponding sensed increase in activity.
 6. The method ofclaim 1, further comprising evaluating a secondary indicator to confirmthe determination of whether the evaluated ST segment data pointsindicate supply ischemia, wherein the secondary indicator is a positionsensor that provides postural position data.
 7. The method of claim 6,wherein supply ischemia is not indicated if an abrupt postural changecorresponds in time with the indication of the ST data segments.
 8. Themethod of claim 1, wherein determining an ST segment data point furthercomprises: identifying a peak of an R wave; adding a predetermined timeinterval to the identified peak; and identifying a recorded value at atime identified by the predetermined time interval after the peak of theR wave as the ST segment data point.
 9. The method of claim 8, furthercomprising: determining a PR isoelectric baseline value; and subtractingthe PR isoelectric baseline value from the recorded value to identifythe ST segment data point.
 10. The method of claim 1, wherein evaluatingthe ST segment data points further comprises: monitoring the ST segmentdata point values; and initiating a timer interval if a given ST segmentdata point value exceeds a threshold value, wherein determining whetherthe evaluated ST segment data points indicate supply ischemia occursbased upon data collected during the timer interval.
 11. The method ofclaim 10, further comprising: determining a maximum ST segment datapoint value during the timer interval; determining an amount of timefrom initiation of the timer interval until the maximum ST segment datapoint value occurs; and determining that the evaluated ST segment datapoints do not indicate supply ischemia if the amount of time is lessthan a first short value or greater than a first long value.
 12. Themethod of claim 11, further comprising: determining that the evaluatedST segment data points do not indicate supply ischemia if less than apredetermined percentage of the ST segment data points occurring duringthe timer interval exceed the threshold value.
 13. The method of claim11, further comprising: determining that the evaluated ST segment datapoints do not indicate supply ischemia if an ST segment data pointoccurring at a termination of the timer interval is less than apredetermined percentage of the maximum ST segment data value.
 14. Themethod of claim 11, further comprising: calculating a slope of the STsegment data points prior to the maximum ST segment data point; anddetermining that the evaluated ST segment data points do not indicatesupply ischemia if the slope is less than a first slope value.
 15. Anapparatus comprising: means for obtaining an electrogram representingcardiac data from an implantable medical device for a plurality ofcardiac cycles during a period of time; means for monitoring heart rateduring the period of time; means for determining an ST segment datapoint for each of the cardiac cycles; means for evaluating the STsegment data points; means for determining whether the evaluated STsegment data points indicate supply ischemia; means for determiningwhether a trend of a plurality of the ST segment data points tracked atrend of a corresponding plurality of monitored heart rates during theperiod of time; and means for confirming the determination of whetherthe evaluated ST segment data points indicate supply ischemia based onwhether the trend of the plurality of ST segment data points tracked thetrend of the plurality of monitored heart rates.
 16. The apparatus ofclaim 15, further comprising means for detecting demand ischemia whenthe trend of the plurality of ST segment data points tracked the trendof the plurality of monitored heart rates.
 17. The apparatus of claim15, further comprising: means for sensing respiration; means for sensingactivity; means for sensing and evaluating a secondary indicator toconfirm the determination of whether the evaluated ST segment datapoints indicate supply ischemia; and means for evaluating the sensedactivity and sensed respiration as the secondary indicator anddetermining supply ischemia if indicated by the ST segment data pointsand an increase respiration rate does not correlate with the sensedactivity level.
 18. The apparatus of claim 15, further comprising meansfor monitoring patient posture and determining that supply ischemia isnot present if a variation in the ST segment data points correlates withan abrupt change in posture.
 19. The method of claim 1, whereinmonitoring the heart rate comprises determining a plurality of heartrate values during the period of time, and wherein determining whether atrend of a plurality of the ST segment data points tracked a trend of acorresponding plurality of monitored heart rates comprises determiningan amount of correlation between the trend of the plurality of heartrate values and the trend of the ST segment data points.
 20. Theapparatus of claim 15, wherein means for monitoring heart rate comprisesmeans for determining a plurality of heart rate values during the periodof time, and wherein means for determining whether a trend of aplurality of the ST segment data points tracked a trend of acorresponding plurality of monitored heart rates comprises means fordetermining an amount of correlation between the trend of the pluralityof heart rate values and the trend of the ST segment data points. 21.The apparatus of claim 15, further comprising means for ruling out adetermination of supply ischemia when the trend of the plurality of STsegment data points tracked the trend of the plurality of monitoredheart rates.